The present invention relates generally to extracting motion vectors from a sequence of video frames, and more particularly, to detecting unusual events in videos.
Compressed Video Formats
Basic standards for compressing the bandwidth of digital color video signals have been adopted by the Motion Picture Experts Group (MPEG). The MPEG standards achieve high data compression rates by developing information for a full frame of the image only every so often. The full image frames, i.e. intra-coded frames, are often referred to as xe2x80x9cI-framesxe2x80x9d or xe2x80x9canchor frames,xe2x80x9d and contain full frame information independent of any other frames. Image difference frames, i.e. inter-coded frames, are often referred to as xe2x80x9cB-framesxe2x80x9d and xe2x80x9cP-frames,xe2x80x9d or as xe2x80x9cpredictive frames,xe2x80x9d and are encoded between the I-frames and reflect only image differences i.e. residues, with respect to the reference frame.
Typically, each frame of a video sequence is partitioned into smaller blocks of picture element, i.e. pixel, data. Each block is subjected to a discrete cosine transformation (DCT) function to convert the statistically dependent spatial domain pixels into independent frequency domain DCT coefficients. Respective 8xc3x978 or 16xc3x9716 blocks of pixels, referred to as xe2x80x9cmacro-blocks,xe2x80x9d are subjected to the DCT function to provide the coded signal.
The DCT coefficients are usually energy concentrated so that only a few of the coefficients in a macro-block contain the main part of the picture information. For example, if a macro-block contains an edge boundary of an object, the energy in that block after transformation, i.e., as represented by the DCT coefficients, includes a relatively large DC coefficient and randomly distributed AC coefficients throughout the matrix of coefficients.
A non-edge macro-block, on the other hand, is usually characterized by a similarly large DC coefficient and a few adjacent AC coefficients which are substantially larger than other coefficients associated with that block. The DCT coefficients are typically subjected to adaptive quantization, and then are run-length and variable-length encoded for the transmission medium. Thus, the macro-blocks of transmitted data typically include fewer than an 8xc3x978 matrix of codewords.
The macro-blocks of inter-coded frame data, i.e. encoded P or B frame data, include DCT coefficients which represent only the differences between a predicted pixels and the actual pixels in the macro-block. Macro-blocks of intra-coded and inter-coded frame data also include information such as the level of quantization employed, a macro-block address or location indicator, and a macro-block type. The latter information is often referred to as xe2x80x9cheaderxe2x80x9d or xe2x80x9coverheadxe2x80x9d information.
Each P frame is predicted from the lastmost occurring I or P frame. Each B frame is predicted from an I or P frame between which it is disposed. The predictive coding process involves generating displacement vectors, often referred to as xe2x80x9cmotion vectors,xe2x80x9d which indicate the magnitude of the displacement to the macro-block of an I frame most closely matches the macro-block of the B or P frame currently being coded. The pixel data of the matched block in the I frame is subtracted, on a pixel-by-pixel basis, from the block of the P or B frame being encoded, to develop the residues. The transformed residues and the vectors form part of the encoded data for the P and B frames.
Older video standards, such as ISO MPEG-1 and MPEG-2, are relatively low-level specifications primarily dealing with temporal and spatial compression of video signals. With these standards, one can achieve high compression ratios over a wide range of applications. Newer video coding standards, such as MPEG-4, see xe2x80x9cInformation Technologyxe2x80x94Generic coding of audio/visual objects,xe2x80x9d ISO/IEC FDIS 14496-2 (MPEG4 Visual), November 1998, allow arbitrary-shaped objects to be encoded and decoded as separate video object planes (VOP). These emerging standards are intended to enable multimedia applications, such as interactive video, where natural and synthetic materials are integrated, and where access is universal. For example, one might want to extract features from a particular type of video object, or to perform for a particular class of video objects.
With the advent of new digital video services, such as video distribution on the INTERNET, there is an increasing need for signal processing techniques for identifying information in video sequences, either at the frame or object level, for example, identification of activity.
Feature Extraction
Previous work in feature extraction for video indexing from compressed data has primarily emphasized DC coefficient extraction. In a paper entitled xe2x80x9cRapid Scene Analysis on Compressed Video,xe2x80x9d IEEE Transactions on Circuits and Systems for Video Technology, Vol. 5, No. 6, December 1995, page 533-544, Yeo and Liu describe an approach to scene change detection in the MPEG-2 compressed video domain. The authors also review earlier efforts at detecting scene changes based on sequences of entire uncompressed image data, and various compressed video processing techniques of others. Yeo and Liu introduced the use of spatially reduced versions of the original images, so-called DC images, and DC sequences extracted from compressed video to facilitate scene analysis operations. Their xe2x80x9cDC imagexe2x80x9d is made up of pixels which are the average value of the pixels in a block of the original image and the DC sequence is the combination of the reduced number of pixels of the DC image. It should be noted that the DC image extraction based technique is good for I-frames since the extraction of the DC values from I-frames is relatively simple. However, for other type frames, additional computation is needed.
Won et al, in a paper published in Proc. SPIE Conf. on Storage and Retrieval for Image and Video Databases, January 1998, describe a method of extracting features from compressed MPEG-2 video by making use of the bits expended on the DC coefficients to locate edges in the frames. However, their work is limited to I-frames only.
Kobla et al describe a method in the same Proceedings using the DC image extraction of Yeo et al to form video trails that characterize the video clips.
Feng et al. (IEEE International Conference on Image Processing, Vol. II, pp. 821-824, Sep. 16-19, 1996), use the bit allocation across the macro-blocks of MPEG-2 frames to detect abrupt scene changes, without extracting DC images. Feng et al.""s technique is computationally the simplest since it does not require significant computation beyond that required for parsing the compressed bit-stream.
U.S. patent Applications entitled xe2x80x9cMethods of scene change detection and fade detection for indexing of video sequences,xe2x80x9d (application Ser. No. 09/231,698, filed Jan. 14, 1999), xe2x80x9cMethods of scene fade detection for indexing of video sequences,xe2x80x9d (application Ser. No. 09/231,699, filed Jan. 14, 1999), xe2x80x9cMethods of Feature Extraction for Video Sequences,xe2x80x9d (application Ser. No. 09/236,838, Jan. 25, 1999), describe computationally simple techniques which build on certain aspects of Feng et al.""s approach and Yeo et al""s approach to give accurate and simple scene change detection.
After a suspected scene or object change has been accurately located in a group of consecutive frames by use of a DC image extraction based technique, application of an appropriate bit allocation-based technique and/or an appropriate DC residual coefficient processing technique to P or B-frame information in the vicinity of the located scene quickly and accurately locates the cut point. This combined method is applicable to either MPEG-2 frame sequences or MPEG-4 multiple object sequences. In the MPEG-4 case, it is advantageous to use a weighted sum of the change in each object of the frame, using the area of each object as the weighting factor.
U.S. patent application Ser. No. 09/345,452 entitled xe2x80x9cCompressed Bit-Stream Segment Identification and Descriptor,xe2x80x9d filed by Divakaran et al. on Jul 1, 1999 describes a technique where magnitudes of displacements of inter-coded frames are determined based on the number bits in the compressed bit-stream associated with the inter-coded frames. The inter-coded frame includes macro-blocks. Each macro-block is associated with a respective portion of the inter-coded frame bits which represent the displacement from that macro-block to the closest matching intra-coded frame. The displacement magnitude is an average of the displacement magnitudes of all the macro-blocks associated with the inter-coded frame. The displacement magnitudes of those macro-blocks which are less than the average displacement magnitude are set to zero. The number of run-lengths of zero magnitude displacement macro-blocks is determined to identify the first inter-coded frame.
Activity
Work done so far has focussed on extraction of motion information, and using the motion information for low level applications such as detecting scene changes. There still is a need to extract features for higher level applications. For example, there is a need to extract features that are indicative of the nature of the activity and unusual events in a video sequence. A video or animation sequence can be perceived as being a slow sequence, a fast paced sequence, an action sequence, and so forth.
Examples of high activity include scenes such as goal scoring in a soccer match, scoring in a basketball game, a high speed car chase. On the other hand, scenes such as news reader shot, an interview scene, or a still shot are perceived as low action shots. A still shot is one where there is little change in the activity frame-to-frame. Video content in general spans the gamut from high to low activity. It would also be useful to be able to identify unusual events in a video related to observed activities. The unusual event could be a sudden increase or decrease in activity, or other temporal variations in activity depending on the application.
A method and system detect an unusual event in a video. Motion vectors are extracted from each frame in a video acquired by a camera of a scene. Zero run-length parameters are determined for each frame from the motion vectors. The zero run-length parameters are summed over predetermined time intervals of the video, and a distance is determined between the sum of the zero run-lengths of a current time interval and the sum of the zero run-lengths of a previous time interval. Then, the unusual event is detected if the distance is greater than a predetermined threshold.
The zero run-length parameters can be classified into short, medium and long zero run-lengths, and the zero run-length parameters are normalized with respect to a width of each frame of the video so that the zero run-length parameters express the number, size, and shape of distinct moving objects in the video.